"How to find people on Facebook" matching MCP servers:

Enables AI assistants to search a public Facebook post archive using keyword, semantic, and hybrid retrieval, browse recently indexed posts, and fetch individual post records with source links through read-only MCP tools.

Open MCP server for AI agents to discover people, jobs, collaborators and projects through semantic search over human-published context.

This read-only MCP Server allows you to connect to Facebook data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

Memory vaults on your own machine, one per life domain, retrieved with a local BM25 index fused with vector search, where the human decides which vaults a model may answer from. Requires the Mnemosyne OS desktop app running locally; it also reports what other coding agents on the same machine are doing.

Enables AI agents to find and query real-time GitHub coding bounties with built-in scam filtering, supporting listing, matching, and detailed bounty retrieval.

Enables semantic search over local markdown specs, RFCs, and docs using Ollama and LanceDB, allowing AI agents to find relevant information by meaning rather than exact keywords.

Local MCP server that turns Mark Builds Brands' YouTube knowledge into an AI coaching assistant for ecommerce and Facebook Ads.

Read-only recall over your past Claude Code, Codex, pi and Hermes sessions: semantic search for past decisions, rationale and findings, plus tools to list sessions, get the gist of one, find exact strings in it and read its turns. Works on your local memory or on any memory published as a Hugging Face dataset.

A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.

Provides semantic search and access to Contraption Company blog posts and essays. Uses AI-powered embeddings to find relevant content and supports real-time updates via webhooks.

Read-only semantic retrieval for agents that need to find the right Obsidian note without write access.

Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

Provides code repository indexing and semantic search capabilities, allowing natural language queries to find relevant code snippets with automatic incremental indexing and multi-language support.

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Enables semantic search across multiple knowledge datasets using FAISS vector embeddings, allowing natural language queries to find relevant documents with fast retrieval.

Enables Claude Code to perform local hybrid search over Obsidian vaults, discover and list projects, read notes with links and backlinks, and find notes by ticket key while keeping the index private on the machine.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

Advanced content gap analysis using Query Decomposition and Keyword Fan-Out (Google's patented methodology). Tells you exactly what user queries your content covers - and what it misses. Built on academic research because I needed to understand how AI search engines actually evaluate content.

Find, run, and manage your local AI models, then talk to your files, your code, and the sites you crawl. Every answer cites the source, it all runs on your own machine, and it's one program with nothing else to set up.

A Model Context Protocol server that runs on Cloudflare Workers with OAuth login, allowing clients like Claude Desktop to connect to it for tool-augmented AI interactions.

A Model Context Protocol server that provides AI assistants with access to Glean's enterprise knowledge features, including content search, people directory, and AI chat capabilities.

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Enables Claude Desktop and other AI tools to interact directly with Figma, allowing for powerful AI-assisted design capabilities through natural language commands.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

Enables agents to find relevant documentation with source URLs, evidence, and freshness, search and browse an llms.txt directory, validate or draft llms.txt files, and manage site registration, verification, and change watches.

Enables AI assistants and developer tools to securely access and interact with an organization's enterprise knowledge, documents, and people through natural language while respecting existing access permissions.

Enables creation and management of AI-powered web entity collections (companies, people, research papers) with automated search, data enrichment, monitoring, and verification through Exa's Websets API.